PhD position on machine learning based predictions of river flow and water temperature in a changing climate
Publication date:
02 October 2024Workload:
100%- Place of work:Zurich
PhD position on machine learning based predictions of river flow and water temperature in a changing climate | |
Published | 1 October 2024 |
Workplace | Zurich, Zurich region, Switzerland |
Category | Environment Pedagogy |
Position | Junior Researcher / PhD Position |
PhD position on machine learning based predictions of river flow and water temperature in a changing climate 100%, Zurich, fixed-termThe Land-Climate Dynamics group at ETH Zürich is looking for a Doctoral candidate to leverage machine learning to investigate changes in Swiss water temperatures and river flow in support of energy system science.The Land-Climate Dynamics group at ETH Zürich is looking for a Doctoral candidate to leverage machine learning to investigate changes in Swiss water temperatures and river flow in support of energy system science. Project backgroundBoth river flow volumes and water temperature are essential factors in the energy system as they directly influence generation of hydropower and impact the cooling efficiency of thermal power plants. In Switzerland, anthropogenic climate change is affecting both water quantity and temperatures in rivers and streams thereby raising legitimate questions on associated risks to the energy system. To advance our understanding of climate change impacts on water flow volumes and temperature, the goal is to build on recent advances in using machine learning for hydrological modelling to develop spatially contiguous data-driven models of daily water temperature and river flow in Switzerland. These will be linked with climate projections to investigate to what extent climate change is increasing the risk of riverine heatwaves - relevant to thermal power plants - and hydrological droughts - which may be a threat to hydropower production. The research will be conducted within the RECIPE (Resilient Infrastructure for the Swiss Energy Transition) project that is funded by the SWiss Energy research for the Energy Transition (SWEET ) program in collaboration with the National Centre for Climate Services (NCCS) . Job descriptionAs a doctoral student you will conduct quantitative and theoretical research at the interface between hydrological and climate sciences and investigate approaches that allow for a joint prediction of flow volumes and water temperatures at ungauged locations in Switzerland. This involves applying deep learning methods to in-situ observations and to use the resulting models in together with climate model simulations to explore past and future extremes of flow volumes and water temperatures across Switzerland. Profile
Workplace We offer
Working, teaching and research at ETH Zurich We value diversityIn line with our values , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.
Curious? So are we.We look forward to receiving your online application with the following documents:
Screening of applications will start end of October. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered. Further information about the institute for Atmospheric and Climate Science can be found on our website . Questions regarding the position should be directed to Lukas Gudmundsson, lukas.gudmundsson@ env.ethz.ch (no applications). Administrative requests should be directed to Rahel Buri, rahel.buri@ env.ethz.ch . Apply online now | |
In your application, please refer to myScience.ch and referenceJobID65497. |